tensorflow lite

The article shows how to run practical AI automations on low‑powered Linux boxes (Raspberry Pi, old minis) by picking efficient models and using quantization and lean runtimes (ONNX Runtime, TFLite/OpenVINO). It details containerized deployment, cron/systemd scheduling, MQTT messaging, caching, and monitoring, with examples like vision, speech, and anomaly detection that deliver useful results on minimal budgets and watts.